Background: Increasing epidemiologic and experimental evidence supports the role of inorganic arsenic in the development of diabetes. Arsenic in drinking water is a major concern for US populations who live in small rural communities. Prospective evidence and mechanisms for arsenic related diabetes must be investigated. Objective: To evaluate the role of inorganic arsenic exposure and metabolism and gene-arsenic interactions in the development of diabetes, insulin resistance, ? cell dysfunction and the metabolic syndrome among 2,717 Strong Heart Family Study (SHFS) participants e18 year old who were free of diabetes at baseline. Preliminary studies: We have identified an association between urine arsenic concentrations and the prevalence of diabetes in American Indians 45-74 year old from Arizona, Oklahoma and the Dakotas who participated in the Strong Heart Study (SHS). Urine arsenic concentrations and methylation excretion patterns remained constant over a 10-year follow-up. The heritability of the proportion of monomethylarsonate (%MMA) in urine was 0.52. In a small linkage study, we detected potential quantitative trait loci associated with %MMA in areas of the genome close to methyltransferase genes. Design and setting: The SHFS is a population- based prospective family study that recruited parents, spouses, offspring, spouses of offspring and grandchildren of SHS participants in 1998-2005. Demographic, lifestyle and medical information and measures of fasting glucose and insulin, lipid profile, hypertension endpoints, body mass index, and waist and hip circumferences are available at baseline and follow-up visits through 2011. Urine samples and blood DNA samples were stored at -70oC. Exposure assessment: We will measure total urine arsenic and urine arsenic species concentrations using inductively coupled plasma-mass spectrometry (ICPMS) and high performance liquid chromatography-ICPMS (HPLC-ICPMS), respectively. Genetic assessment: We will prioritize and measure ~1,500 SNPs in candidate genes related to arsenic metabolism and toxicity using a multiplex panel. We will measure SNPs in candidate genes related to diabetes traits using the Metabo-chip, a highly cost- effective candidate gene chip for diabetes and cardiometabolic traits. Statistical analysis: We will use mixed- effect models for binary and linear outcomes to assess the prospective association of urine arsenic species concentrations at baseline with the incidence of diabetes and the metabolic syndrome and changes in the homeostatic model assessment to quantify insulin resistance (HOMA-IR) and ? cell dysfunction (HOMA-B) over time. Gene-arsenic interaction will be estimated using principle component analysis and accounting for population stratification using genomic control. Significance: By investigating the contribution of inorganic arsenic to diabetes, insulin resistance, ? cell dysfunction and the metabolic syndrome and by identifying genetic susceptibility factors, this study can inform the arsenic-diabetes relationship and impact the prevention and control of arsenic exposure in drinking water and food in the US and abroad.